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International Society for Environmental Information Sciences

Environmental Informatics Archives

ISSN 1811-0231 / ISEIS Publication Series Number P002

Copyright © 2006 ISEIS. All rights reserved.



  Paper EIA06-028, Volume 4 (2006), Pages 312-323 = complimentary

Spectral Enhancement and Automated Extraction from Kentucky’s NAIP Imagery of Potential Sinkhole Features, Trigg County, Kentucky, USA--Initial Investigations

J. S. Dinger1, D. P. Zourarakis2 and J. C. Currens1

1. Kentucky Geological Survey, University of Kentucky, Lexington, Kentucky, USA, 40506-0107.

2. Kentucky Division of Geographic Information Commonwealth Office of Technology-Division of Geographic Information 1025 Capital Center Dr. Suite 101-Frankfort KY 40601 502-573-1450.



In eastern USA, karst sinkholes are responsible for millions of dollars of damage to buildings, infrastructure, agribusiness, and land availability. Geophysical techniques have been employed to locate developing sinkholes that have not yet expressed themselves at land surface through cover collapse, but these techniques are expensive and time consuming.. This paper presents initial research into locating cover-collapse sinkholes through the use of aerial remote sensing. The summer of 2004, National Agricultural Imagery Program imagery, 1-m ground resolution, in 3 bands (visible, RGB), with 8 pixels per band is effective in highlighting circular features that appear to be related to sinkhole occurrence on two farm sites. In some instances, the features were sinkholes up to 5 m in depth. In other instances, the features did not represent existing sinkholes but potential sites of incipient cover collapse. Differences in agriculturally related vegetative cover at this time affected the efficiency of determining the extent of karst development. Surface geophysical techniques will be used to characterize the subsurface when cropping practices allow. The goal is to correlate imagery features to subsurface characteristics so that remotely sensed imagery can be used as a means of delineating potential cover-collapse sinkholes before they express themselves at the surface. Development of such a tool will provide a time- and cost-effective approach to land use planning and, therefore, substantially reduce damage done by cover collapse.

Keywords: remote sensing, imagery, karst, sinkholes, linear, cover collapse, spectral enhancement, feature extraction


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